Search Results (40,386)

Curcumin, a natural polyphenol derived from Curcuma longa L., exhibits diverse biological activities including anti-inflammatory, anticancer, and antioxidant effects, making it a versatile candidate for food, feed, pharmaceutical, and cosmetic applications. However, its industrial application is hindered by low bioavailability, poor water solubility, and high production costs. This review comprehensively summarizes the latest advances in curcumin’s physicochemical properties, production routes (phytoextraction, chemical synthesis, and microbial biosynthesis), and wide applications. Compared with existing reviews, this work emphasizes quantitative benchmarking of production methods (yield, productivity, and environmental metrics), critical evaluation of application feasibility including regulatory hurdles and clinical evidence, and actionable future directions for industrial scalability. We systematically analyze the advantages, limitations, economic and environmental trade-offs of each production route, and highlight recent innovations in bioavailability enhancement and metabolic engineering. This review aims to provide a holistic theoretical and technical framework for accelerating curcumin’s sustainable development and commercialization in high-value products. Full article

As an emerging threat to global food security, wheat blast necessitates the development of a rapid and field-deployable detection system to facilitate early diagnosis, enable effective management, and prevent its further spread to new regions. In this study, we aimed to validate and improve a Recombinase Polymerase Amplification coupled with PCRD lateral flow detection (RPA-PCRD strip assay) kit for the rapid and specific identification of Magnaporthe oryzae pathotype Triticum (MoT) in field samples. The assay demonstrated exceptional sensitivity, detecting as low as 10 pg/µL of target DNA, and exhibited no cross-reactivity with M. oryzae Oryzae (MoO) isolates and other major fungal phytopathogens under the genera of Fusarium, Bipolaris, Colletotrichum, and Botrydiplodia. The method successfully detected MoT in wheat leaves as early as 4 days post-infection (DPI), and in infected spikes, seeds, and alternate hosts. Furthermore, by combining a simplified polyethylene glycol-NaOH method for extracting DNA from plant samples, the entire RPA-PCRD strip assay enabled the detection of MoT within 30 min with no specialized equipment and high technical skills at ambient temperature (37–39 °C). When applied to field samples, it successfully detected MoT in naturally infected diseased wheat plants from seven different fields in a wheat blast hotspot district, Meherpur, Bangladesh. Training 52 diverse stakeholders validated the kit’s field readiness, with 88% of trainees endorsing its user-friendly design. This method offers a practical, low-cost, and portable point-of-care diagnostic tool suitable for on-site genomic surveillance, integrated management, seed health testing, and quarantine screening of wheat blast in resource-limited settings. Furthermore, the RPA-PCRD platform serves as an early warning modular diagnostic template that can be readily adapted to detect a wide array of phytopathogens by integrating target-specific genomic primers. Full article

Automatic parking in constrained environments, such as dead-end roads and narrow parallel spaces, remains a challenge due to the low success rate and poor real-time performance of conventional planning algorithms. The paper proposes an entry-point guided path planning method that integrates heuristic search with hybrid A* and reeds-shepp curve to address the above limitations. By rapidly identifying the optimal initial parking pose, the proposed method ensures the kinematic feasibility and smoothness of the resulting trajectories. To further improve efficiency and safety in tight spaces, a hybrid collision detection mechanism is developed by combining a rectangular envelope with multi-circle fitting. The hierarchical geometric modeling approach significantly reduces computational cost while maintaining high detection accuracy. The method is validated through both simulations and real-vehicle experiments in vertical and parallel parking scenarios. Results demonstrate that in typical constrained scenarios, the average planning time is only 0.543 s, and the number of direction changes is maintained between 1 and 6, demonstrating superior computational efficiency and improved trajectory smoothness. These attributes make the algorithm highly suitable for practical deployment in advanced driver assistance systems and autonomous vehicles. Full article

In this study, dried biomass of the alga Chlorella vulgaris was ground into a powder as an eco-friendly, low-cost inhibitor to mitigate the corrosion of carbon steel in acidic solutions. Electrochemical and weight loss measurements, surface morphology observations, adsorption isotherms, activation energy, and potential of zero charge calculations were applied to evaluate the inhibition performance. Electrochemical results indicate that C. vulgaris powder can simultaneously inhibit both the anodic and cathodic corrosion processes of carbon steel, demonstrating good inhibition performance and classifying it as a mixed-type inhibitor with both anodic and cathodic characteristics. Weight loss data further confirm that at a concentration of 300 mg/L, the corrosion inhibition efficiency reaches 88%. The fitted adsorption isotherm reveals that the adsorption of Chlorella vulgaris powder on the carbon steel surface follows the Langmuir model. Density functional theory (DFT) and molecular dynamics simulations indicate that the excellent inhibition performance is attributed to the combined effects of physisorption and chemisorption of constituents such as amino acids and cellulose present in C. vulgaris. Full article

Antimicrobial resistance (AMR) is a major global health concern, which complicates treatment of microbial infections and wounds. Conventional therapies are no longer effective against drug resistant microbes; hence, novel antimicrobial approaches are urgently required. Silver nanoparticles (AgNPs) offer stronger antimicrobial activity, and in situ synthesis improves stability, uniformity, cost efficiency, and bioactivity while minimising contamination. These features make AgNPs well-suited for incorporation into textiles and wound dressings. Red wine extract (RW-E), rich in antioxidant and anti-inflammatory compounds was used to hydrothermally synthesise RW-AgNPs and RW-AgNPs-loaded on cotton (RWALC) by optimising pH and RW-E concentration. Characterisation was performed using UV–Vis spectroscopy, dynamic light scattering (DLS), and High Resolution and Scanning electron microscopy (HR-TEM and SEM). Antibacterial activities were evaluated against human pathogens through agar disc diffusion assay for RWALC and microdilution assay for RW-AgNPs. RWALC showed higher potency against both Gram-negative and Gram-positive bacteria, with inhibition zones of 12.33 ± 1.15 to 23.5 ± 5.15 mm, that surpassed those of ciprofloxacin (10 ± 3 to 19.17 ± 1.39 mm at 10 μg/mL). RW-AgNPs exhibited low minimum inhibitory concentrations (MIC: 0.195–3.125 μg/mL) and minimum bactericidal concentrations (MBC: 0.78–6.25 μg/mL). Preincubation with β-mercaptoethanol (β-ME) inhibited the antibacterial activity of RWALC, suggesting that thiolated molecules are involved in AgNPs-mediated effects. This study demonstrated that green-synthesised RW-AgNPs, incorporated in situ into cotton, conferred strong antibacterial properties, warranting further investigation into their mechanisms of action. Full article

The deployment of large remotely operated vehicles (ROVs) or autonomous underwater vehicles (AUVs) typically requires support vessels, crane systems, and specialized personnel, resulting in increased logistical complexity and operational costs. In this context, lightweight and modular underwater robots have emerged as a cost-effective alternative, capable of reaching significant depths and performing tasks traditionally associated with larger platforms. This article presents a system architecture for recovering a known object using a hybrid-controlled ROV, integrating autonomous perception, high-level interaction, and low-level control. The proposed architecture includes a perception module that estimates the object pose using a Perspective-n-Point (PnP) algorithm, combining object segmentation from a YOLOv11-seg network with 2D keypoints obtained from a YOLOv11-pose model. In addition, a Natural Language ROS Agent is incorporated to enable high-level command interaction between the operator and the robot. These modules interact with low-level controllers that regulate the vehicle degrees of freedom and with autonomous behaviors such as target approach and grasping. The proposed system is evaluated through simulation and experimental tank trials, including object recovery experiments conducted in a 12 × 8 × 5 m test tank at CIRTESU, as well as perception validation in simulated, tank, and harbor scenarios. The results demonstrate successful recovery of a black box using a BlueROV2 platform, showing that architectures of this type can effectively support operators in underwater intervention tasks, reducing operational risk, deployment complexity, and mission costs. Full article

Normalization is a critical step in Multiple-Criteria Decision Analysis (MCDA) because it transforms heterogeneous criterion values into comparable information. This study examines normalization techniques through the lens of entropy, highlighting how criterion data structure shapes normalization behavior and ranking stability within TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Seven widely used normalization procedures are analyzed regarding mathematical properties, sensitivity to extreme values, treatment of benefit and cost criteria, and rank reversal. Normalization is treated as a source of uncertainty in MCDA outcomes, as different schemes can produce divergent rankings under identical decision settings. Shannon entropy is employed as a descriptive measure of information dispersion and structural uncertainty, capturing the heterogeneity and discriminatory potential of criteria rather than serving as a weighting mechanism. An illustrative experiment with ten alternatives and four criteria (two high-entropy, two low-entropy) demonstrates how entropy mediates normalization effects. Seven normalization schemes are examined, including vector, max, linear Sum, and max–min procedures. For vector, max, and linear sum, cost-type criteria are treated using either linear inversion or reciprocal transformation, whereas max–min is implemented as a single method. This design separates the choice of normalization form from the choice of cost-criteria transformation, allowing a cleaner identification of their respective contributions to ranking variability. The analysis shows that normalization choice alone can cause substantial differences in preference values and rankings. High-entropy criteria tend to yield stable rankings, whereas low-entropy criteria amplify sensitivity, especially with extreme or cost-type data. These findings position entropy as a key mediator linking data structure with normalization-induced ranking variability and highlight the need to consider entropy explicitly when selecting normalization procedures. Finally, a practical entropy-based method for choosing normalization techniques is introduced to enhance methodological transparency and ranking robustness in MCDA. Full article

To address the challenges of low land use efficiency, soil degradation, and high management costs in Ilex asprella cultivation, this study established an I. asprella–Grona styracifolia intercropping system and systematically evaluated its effects on soil nutrient cycling, microbial communities, and crop growth. Field experiments were conducted in Yunfu City, Guangdong Province, with monoculture (LCK for I. asprella, DCK for G. styracifolia) and three intercropping densities (HDT, LDT, MDT). Combining 16S rRNA sequencing and metagenomics, we analyzed the functional profile of the rhizosphere microbiome. The results showed that intercropping significantly increased the biomass of G. styracifolia, with the medium-density (MDT) treatment increasing plant length and fresh weight by 41.2% and 2.4 times, respectively, compared to monoculture. However, high-density intercropping suppressed the accumulation of medicinal compounds. In terms of soil properties, intercropping significantly enhanced soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and available nitrogen (AN) in the rhizosphere of both plants. Specifically, AN in the I. asprella rhizosphere increased by 18.9%. Soil urease and acid phosphatase activities were also elevated, while pH decreased. Microbial analysis revealed that intercropping reshaped the rhizosphere microbial community structure, significantly increased the Shannon diversity index of bacteria in the G. styracifolia rhizosphere, and enhanced the complexity of the microbial co-occurrence network. Metagenomic analysis further confirmed that intercropping enriched functional genes related to carbon fixation, nitrogen cycling (nitrogen fixation, assimilatory nitrate reduction), and organic phosphorus mineralization (the phoD gene), thereby driving the transformation and availability of soil nutrients. These findings demonstrate that the I. asprella–G. styracifolia intercropping system, particularly at medium density, effectively improves soil fertility and land use efficiency by regulating rhizosphere microbial functions, providing a theoretical basis for the sustainable ecological cultivation of I. asprella. Full article

Transparent polymeric materials such as poly(methyl methacrylate) (PMMA), polycarbonate (PC), and polyethylene terephthalate (PET) are widely used as glass alternatives in algal bioreactors, where optical clarity and mechanical stability are crucial. However, their long-term use is limited by surface degradation processes. Photodegradation, hydrolysis, and biofilm accumulation can reduce light transmission in the 400–700 nm range essential for photosynthesis. This study examined the aging of PMMA, PC, and PET under bioreactor conditions. Samples were exposed for 70 days to illumination, culture medium, and aquatic environments. Changes in their optical transmittance, surface roughness, and wettability were analyzed. All polymers exhibited measurable surface degradation, characterized by an average 15% loss in transparency, significant increases in surface roughness, and reduced contact angles. PMMA demonstrated the highest optical stability, maintaining strong transmission in key blue and red spectral regions, while PET performed the worst, showing low initial clarity and the steepest decline. The most severe surface degradation occurred in areas exposed to the receding liquid interface, highlighting the need for targeted cleaning and/or a reduction in the size of the liquid–vapor transition zone. Overall, the results identify PMMA and recycled PMMA (PMMA_R) as durable, cost-effective materials for transparent bioreactor walls. Full article

In the realm of wearable technology, achieving robust continuous authentication requires balancing high security with the strict resource constraints of embedded platforms. Conventional machine learning approaches and deep learning-based biometrics often incur high computational costs, making them unsuitable for low-power edge devices. To address this challenge, we propose H-PPG, a lightweight authentication system that integrates photoplethysmography (PPG) and inertial measurement unit (IMU) signals for continuous user verification. Using Hyperdimensional Computing (HDC), a lightweight classification framework inspired by brain-like computing, H-PPG encodes user physiological and motion data into high-dimensional hypervectors that comprehensively represent individual identity, enabling robust, efficient and lightweight authentication. An adaptive learning process is employed to iteratively refine the user’s hypervector, allowing it to progressively capture discriminative information from physiological and behavioral samples. To further enhance identity representation, a dimension regeneration mechanism is introduced to maximize the information capacity of each dimension within the hypervector, ensuring that authentication accuracy is maintained under lightweight conditions. In addition, a user-defined security level scheme and an adaptive update strategy are proposed to ensure sustained authentication performance over prolonged usage. A wrist-worn prototype was developed to evaluate the effectiveness of the proposed approach and extensive experiments involving 15 participants were conducted under real-world conditions. The experimental results demonstrate that H-PPG achieves an average authentication accuracy of 93.5%. Compared to existing methods, H-PPG offers a lightweight and hardware-efficient solution suitable for resource-constrained wearable devices, highlighting its strong potential for integration into future smart wearable ecosystems. Full article

The development of efficient bioelectrodes requires suitable fabrication strategies, starting with the electrode material, which affects the electron transfer between the biocatalyst and the electrode surface. Then, selection and adjustment of the enzyme immobilization conditions are essential to enhance the performance of the bioelectrodes for their desirable utility. In this study, we report the fabrication of a high-performance bioelectrode using a one-step crosslinking of FAD-dependent glucose dehydrogenase (FAD-GDH) and thionine acetate as a redox mediator, with genipin serving as a natural, biocompatible crosslinker. Electrodes were manufactured on flexible polyester substrates using a direct printing technique, enabling reproducible and low-cost production. Among the tested crosslinkers, genipin significantly enhanced the catalytic performance of bioelectrodes. Comparative studies on graphite, silver, and gold electrode materials identified graphite as the most suitable due to its extended electroactive surface area. The developed bioelectrodes applied to glucose biosensing demonstrated a linear amperometric response to glucose in the range of 0.02–2 mM and 0.048–30 mM, covering clinically relevant concentrations. The application of artificial sweat confirmed high detection accuracy. These findings highlight the potential integration of genipin-based enzyme–mediator networks for future non-invasive sweat glucose monitoring platforms. Full article

Video super-resolution (VSR) has advanced rapidly in enhancing video quality and restoring compressed content, yet leading methods often remain too costly for real-world use. We present LIF-VSR, a lightweight, near-real-time framework built with an efficiency-first philosophy, comprising economical temporal propagation, a new neighboring-frame fusion strategy, and three streamlined core modules. For temporal propagation, a uni-directional recurrent architecture transfers context through a compact inter-frame memory unit, avoiding the heavy compute and memory of multi-frame parallel inputs. For fusion and alignment, we discard 3D convolutions and optical flow, instead using (i) a deformable convolution module for implicit feature-space alignment, and (ii) a sparse attention fusion module that aggregates adjacent-frame information via learned sparse key sampling points, sidestepping dense global computation. For feature enhancement, a cross-attention mechanism selectively calibrates temporal features at far lower cost than global self-attention. Across public benchmarks, LIF-VSR achieves competitive results with only 3.06 M parameters and a very low computational footprint, reaching 27.65 dB on Vid4 and 31.61 dB on SPMCs. Full article

Polyethylene is the most used plastic in the world, and over 90% of this plastic is ultimately disposed of in landfills or released into the environment, leading to severe ecological implications. In this research, the technoeconomic feasibility of upcycling low-density polyethylene (LDPE) to produce ethylene is studied. The catalytic conversion of LDPE to ethylene is considered in microwave heating mode and Joule heating mode. Experimental data is obtained under conditions where most of the upcycled products are in the gas phase. A flowsheet is developed that produces industrial quantities of ethylene for both heating modes. A technoeconomic analysis and a life cycle analysis are conducted and compared with the traditional ethane cracking process for producing ethylene. Simulation results indicate that the upcycling system exhibits a lower capital expenditure and a comparable operating expenditure relative to conventional ethane steam cracking while generating additional valuable co-products, such as propylene and aromatic hydrocarbons, leading to a higher net present value potential. Sensitivity analyses reveal that the electricity price has the most significant impact on both the net present value and levelized cost of production, followed by the low-density polyethylene feedstock cost. Life-cycle assessment reveals a substantial reduction in greenhouse-gas emissions in the upcycled process compared to the fossil-based ethane steam-cracking route, primarily due to the use of renewable electricity, the lower reaction temperature that reduces utility demand, and the use of plastic waste as the feedstock. Overall, the proposed process demonstrates strong potential for the sustainable production of ethylene from waste LDPE. Full article

To address the limitations of traditional lithium battery defect detection—low efficiency, high missed detection rates for minute/composite defects, and inadequate multimodal fusion—this study develops an improved YOLOv8 model based on multimodal fusion and attention enhancement for unified full-lifecycle multi-type defect detection. Integrating visible-light and X-ray modalities, the model incorporates a Squeeze-and-Excitation (SE) module to dynamically weight channel features, suppressing redundancy and highlighting cross-modal complementarity. A Multi-Scale Fusion Module (MFM) is constructed to amplify subtle defect expression by fusing multi-scale features, building on established feature fusion principles. Experimental results show that the model achieves an mAP@0.5 of 87.5%, a minute defect recall rate (MRR) of 84.1%, and overall industrial recognition accuracy of 97.49%. It operates at 35.9 FPS (server) and 25.7 FPS (edge) with end-to-end latency of 30.9–38.9 ms, meeting high-speed production line requirements. Exhibiting strong robustness, the lightweight model outperforms YOLOv5/7/8/9-S in core metrics. Large-scale verification confirms stable performance across the battery lifecycle, providing a reliable solution for industrial defect detection and reducing production costs. Full article

The synthesis of carbon dots (CDs) from coal represents a promising strategy for advancing both the efficient, low-carbon utilization of coal resources and the cost-effective production of CDs. To enable the controlled, high-quality conversion of CDs from coal, a comprehensive understanding of the relationship between the coal chemical structure and the properties of CDs is crucial. This study prepared CDs from nine kinds of coal using a chemical oxidation method, and the correlations between properties of coal-based carbon dots and the original materials were revealed. The results show that the luminescence sites of coal-derived CDs are mostly distributed around 435 nm or 500 nm, where the former one relates to the confined sp² domains and the latter one is associated with the defect structure. Coal with a volatile content of about 20–30% in the nine samples was found to produce higher CD yields, with a maximum mass yield of 19.96%, accompanied by stronger fluorescence intensity. During chemical oxidation processes, the unsaturated double bonds (C=C, C=O) and aliphatic chains firstly break, and then aromatic clusters are formed by dehydrocyclization between carbon crystallites, followed by the introduction of a C–O group. The growth of the C–O group in the CDs contributes to a stronger fluorescence property. Furthermore, strong correlations were found between the carbon skeleton structure of raw coal and photoluminescence characteristics of corresponding CDs, as reflected by Raman parameters A_D1/A_G, I_D1/I_G, and FWHM_D. The findings offer significant insights into the precise modulation and control of coal-based carbon dot structures. Full article